Is it still called linear separation with a layer of more than 1 neuron
What you have depicted is a nonlinear classificator. Although each stage does a linear separation, the sequential composition of linear separations is nonlinear. The nonlinearity of the neuron is key in this regard, as otherwise it would all be equivalent to a matrix multiplication, which is linear. You were right about the degree, although it's rarely called like that. People usually describe just the number of layers, and I guess the main reason is that it's not directly equivalent to such polynomials, as that depends on other factors (e.g. the activation function).